Results 11 to 20 of about 109,902 (144)
Aggressive Behavior, Volume 49, Issue 1, Page 85-95, January 2023., 2023 Abstract The past two decades have produced extensive evidence on the manifold and severe outcomes for victims of aggression exposure in the workplace. However, due to the dominating individual‐centered approach, most findings miss a social network perspective.
Alexander Herrmann +2 more
wiley +1 more source
Semi‐supervised classification of fundus images combined with CNN and GCN
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose Diabetic retinopathy (DR) is one of the most serious complications of diabetes, which is a kind of fundus lesion with specific changes. Early diagnosis of DR can effectively reduce the visual damage caused by DR. Due to the variety and different morphology of DR lesions, automatic classification of fundus images in mass screening can ...
Sixu Duan +8 more
wiley +1 more source
Dictionary-based Debiasing of Pre-trained Word Embeddings [PDF]
arXiv, 2021 Word embeddings trained on large corpora have shown to encode high levels of unfair discriminatory gender, racial, religious and ethnic biases. In contrast, human-written dictionaries describe the meanings of words in a concise, objective and an unbiased manner.
arxiv
A Survey On Neural Word Embeddings [PDF]
arXiv, 2021 Understanding human language has been a sub-challenge on the way of intelligent machines. The study of meaning in natural language processing (NLP) relies on the distributional hypothesis where language elements get meaning from the words that co-occur within contexts.
arxiv
Comparative Analysis of Word Embeddings for Capturing Word Similarities [PDF]
6th International Conference on Natural Language Processing (NATP
2020), 2020 Distributed language representation has become the most widely used technique for language representation in various natural language processing tasks. Most of the natural language processing models that are based on deep learning techniques use already pre-trained distributed word representations, commonly called word embeddings.
arxiv +1 more source
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Background This study aims to develop a novel predictive model for determining human papillomavirus (HPV) presence in oropharyngeal cancer using computed tomography (CT). Current image‐based HPV prediction methods are hindered by high computational demands or suboptimal performance.
Junhua Chen +3 more
wiley +1 more source
Task-Specific Dependency-based Word Embedding Methods [PDF]
arXiv, 2021 Two task-specific dependency-based word embedding methods are proposed for text classification in this work. In contrast with universal word embedding methods that work for generic tasks, we design task-specific word embedding methods to offer better performance in a specific task.
arxiv
Artificial Receptor in Synthetic Cells Performs Transmembrane Activation of Proteolysis
Advanced Biology, EarlyView.Transmembrane signaling is the hallmark of living cells and is among the highest challenges for the design of synthetic cells. Herein, an artificial receptor based on the chemistry of self‐immolative linkers is used to communicate information across the lipid bilayer, for transmembrane activation of enzymatic activity. Abstract The design of artificial,
Ane Bretschneider Søgaard +7 more
wiley +1 more source
Spanish Biomedical and Clinical Language Embeddings [PDF]
arXiv, 2021 We computed both Word and Sub-word Embeddings using FastText. For Sub-word embeddings we selected Byte Pair Encoding (BPE) algorithm to represent the sub-words. We evaluated the Biomedical Word Embeddings obtaining better results than previous versions showing the implication that with more data, we obtain better representations.
arxiv
Advanced Biology, EarlyView.Extracellular vesicles (EVs) play a dual role in diagnostics and therapeutics, offering innovative solutions for treating cancer, cardiovascular, neurodegenerative, and orthopedic diseases. This review highlights EVs’ potential to revolutionize personalized medicine through specific applications in disease detection and treatment.
Farbod Ebrahimi +4 more
wiley +1 more source